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Integrated computing curricula combine learning objectives in computing with those in another discipline, like literacy, math, or science, to give all students experience with computing, typically before they must decide whether to take standalone CS courses. One goal of integrated computing curricula is to provide an accessible path to an introductory computing course by introducing computing concepts and practices in required courses. This study analyzed integrated computing curricula to determine which CS practices and concepts are taught, how extensively the curricula are taught, and, by extension, how they might prepare students for later computing courses. The authors conducted a content analysis to examine primary and lower secondary (i.e., K-8) curricula that are taught in non-CS classrooms, have explicit CS learning objectives (i.e., CS+X), and that took 5+ hours to complete. Lesson plans, descriptions, and resources were scored based on frameworks developed from the K-12 CS Framework, including programming concepts, non-programming CS concepts, and CS practices. The results found that curricula most extensively taught introductory concepts and practices, such as sequences, and rarely taught more advanced content, such as conditionals. Students who engage with most of these curricula would have no experience working with fundamental concepts, like variables, operators, data collection or storage, or abstraction in the context of a program. While this focus might be appropriate for integrated curricula, it has implications for the prior knowledge that students should be expected to have when starting standalone computing courses. 

The authors explore the intersection of AI and equity in education, presenting a workshop designed for marginalized youth in urban Mexico. This reflective essay stems from their participation in the International Society for Technology in Education’s AI and education course. The lead author, a language education researcher who emphasizes equity in her scholarship, crafted a presentation on AI’s everyday applications for marginalized Mexican youth. Collaborating organically, the co-authors positioned this project as the course’s final collective output, fostering a unique blend of expertise and community engagement. The lead author designed the presentation for an organization with which she has partnered for over a decade, an educational project that supports learning and life skills, rooted in Don Miguel Ruiz’s Four Agreements, for children who live in a community of unofficial housing on the edge of railroad tracks in Cuernavaca, Mexico. The project aimed to bridge the global application of AI to marginalized Mexicans, facilitating a two-hour workshop in Spring 2023. Two additional faculty, technology education researchers, joined the effort to promote computational literacy equitably through culturally relevant pedagogy. They highlight their diverse scholarly backgrounds, positioning themselves as individuals from the margins, and share their motivation for creating a cogent and engaging workshop for the youth. The lead author reports on the unexpectedly rich conversation that unfolded during the workshop, underscoring the potential for AI to be inclusive as society navigates its integration into education. 

Integrated computing curricula combine learning objectives in computing with those in another discipline, like literacy, math, or science, to give all students experience with computing, typically before they must decide whether to take standalone CS courses. One goal of integrated computing curricula is to provide an accessible path to an introductory computing course by introducing computing concepts and practices in required courses. This paper analyzed integrated computing curricula to determine which CS practices and concepts they teach and how extensively and, thus, how they prepare students for later computing courses. The authors conducted a content analysis to examine primary and lower secondary (i.e., K-8) curricula that are taught in non-CS classrooms, have explicit CS learning objectives (i.e., CS+X), and that took >5 hours to complete. Lesson plans, descriptions, and resources were scored based on frameworks developed from the K-12 CS Framework, including programming concepts, non-programming CS concepts, and CS practices. The results found that curricula most extensively taught introductory concepts and practices, such as sequences, and rarely taught more advanced content, such as conditionals. Students who engage with most of these curricula would have no experience working with fundamental concepts, like variables, operators, data collection or storage, or abstraction in the context of a program. While this focus might be appropriate for integrated curricula, it has implications for the prior knowledge that students should be expected to have when starting standalone computing courses. 

Understanding how human memory and learning works, the differences between beginners and experts, and practical steps developers can take to improve their learning, training, and recruitment.